The state-of-health diagnosis of Li-Co batteries with fuzzy identification

Ho Ta Lin, Tsorng-Juu Liang, Shih Ming Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

This paper employs fuzzy identification for diagnosing battery state of health (SOH) to avoid the inconvenience of battery failure. First, this study performs a life-cycle test of 95 Li-Co batteries with five various discharge currents in order to understand the most important factors that affect battery SOH. The batteries are charged with 0.5C constant-current and constant-voltage hybrid charging, and are discharged with 0.2, 0.4, 0.6, 0.8, and 1 C. The experimental results show that the charging time, the voltage difference between the open circuit and with load, and the voltage change of the battery between the voltage under full discharge and the voltage after the rest for 1 minute can be used to accurately diagnose battery SOH. Since each battery is tested with 300 cycles, the total patterns obtained from the experimental results are 95×300. 1,835 patterns are randomly selected for the fuzzy identification. 60 patterns are also randomly selected for verification. The principle of fuzzy identification as it applies to battery-health diagnosis is based on the principle of closest normal distribution. The average error of the good diagnosis is 1.46%, and the diagnosis standard deviation is 2.36%. The average error with the poor diagnosis and the diagnosis standard deviation are 6.45% and 6.83%, respectively. The results show that the proposed method can accurately diagnose battery health, and thus the state of charge can be more precisely predicted.

Original languageEnglish
Title of host publicationConference Proceedings - 2012 IEEE 7th International Power Electronics and Motion Control Conference - ECCE Asia, IPEMC 2012
Pages2678-2682
Number of pages5
DOIs
Publication statusPublished - 2012 Oct 3
Event2012 IEEE 7th International Power Electronics and Motion Control Conference - ECCE Asia, IPEMC 2012 - Harbin, China
Duration: 2012 Jun 22012 Jun 5

Publication series

NameConference Proceedings - 2012 IEEE 7th International Power Electronics and Motion Control Conference - ECCE Asia, IPEMC 2012
Volume4

Other

Other2012 IEEE 7th International Power Electronics and Motion Control Conference - ECCE Asia, IPEMC 2012
CountryChina
CityHarbin
Period12-06-0212-06-05

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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  • Cite this

    Lin, H. T., Liang, T-J., & Chen, S. M. (2012). The state-of-health diagnosis of Li-Co batteries with fuzzy identification. In Conference Proceedings - 2012 IEEE 7th International Power Electronics and Motion Control Conference - ECCE Asia, IPEMC 2012 (pp. 2678-2682). [6259285] (Conference Proceedings - 2012 IEEE 7th International Power Electronics and Motion Control Conference - ECCE Asia, IPEMC 2012; Vol. 4). https://doi.org/10.1109/IPEMC.2012.6259285